The advanced signal-processing algorithms used in digital hearing aids have improved average hearing aid benefit and satisfaction. However, response to hearing aids is highly variable, with some individuals reporting much more benefit than others. This variability is most evident among older listeners. An important issue is what levels of advanced hearing aid processing are necessary to achieve success with hearing aids in individual listeners. Every form of nonlinear signal processing has its own set of trade-offs of improved audibility versus increased modification of the signal caused by the signal processing. However, there are no effective procedures for determining who will benefit from the processing or how the processing should be adjusted for the individual listener. The long term goal of this research is use evidence-based clinical tests to guide the selection of signal processing that is most appropriate for individual older adults wearing hearing aids in their own listening environments. The first specific aim of this study is to characterize variability in response to signal manipulation among older adults and to determine what patient factors are related to that variability. The first experiment measures response to signal modification caused by several types of hearing aid processing under controlled laboratory conditions and relates those responses to patient factors. The second experiment extends those concepts to wearable hearing aids in the listener's own environment. The second specific aim is to determine prospectively the appropriate level of hearing-aid signal manipulation for an individual and to validate that determination, under clinical conditions. The third experiment will translate the results from the first two experiments into a set of patient tests that can be used clinically to predict the optimal signal processing for an individual. Listener response to hearing aid signal processing will include aided speech intelligibility, aided sound quality, and/or perceived reduction of hearing handicap. Patient factors will include the audiogram, spectral-temporal processing abilities, and cognitive abilities.